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95% Confidence Intervals of categorical outcome by categories of a Risk Factor in Survey Data

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Use the following program to generate the summary 95% confidence intervals Usage RESULTS You get the N for each category of race, and the Percent and 95% CI for each category of BMI. The First row depicts the order of the results

Easy Estimates Table after Logistic Regression

Regression Models

We need to address several concerns when running logistic regression in Stata. For such situation, the fantastic esttab and estout packages are incredibly useful. An example follows One thing to note, the Variables are not displayed, only their categories. It may prove to be problematic if many variables use same

RAAB6 Surveys Stata Commands for Cataract Surgical Outcomes

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The WHO Eye Care Indicator Menu has prescribed many core indicators. The Core Indicator 6 is Cataract surgical outcome (visual acuity) in the domain of Output – Eye Care Service Quality Definition: Percentage of eyes with: Estimation of these indicators can be accomplished using the below Stata code I have

Stata Code for eCSC and CSC calculations

WHO has identified WHO Effective Cataract Surgical Coverage (eCSC) as a key indicator for monitring Universal Eye Health. LINK There is a slight change from the prior formulae used for eCSC in papers by Ramke et al and the one published by Keel et al. Further, the original CSC estimation

Match string for patterns

One can use Regular Expressions (RegEx) in Stata functions when working with string data Finding whether a String matches a Pattern One can use the ustrregexm function. You can remember it as an abbreviation for "Unicode String Regular Expression Match" = UStrRegExM The above function will be TRUE if the

Using the results of Stata Direct Standardization for display, HTML, putExcel etc

The dstdize command saves certain matrices and scalars. these can be used to access the results and programmatically write them to docx, excel, html files etc Example Usage

Age-Sex Direct Standardization in Stata

When using person level / individual level data (not aggregated data), quick reference commands are: Age standardization within sex proportion msvi, stdize(ageGrp) stdweight(per) over(sex) per = percent of population in age group calculated separately for males and femalesdstdize msvi p ageGrp if sex==1, by(sex) using(stdPop) print AND dstdize msvi p

Tests for Trends in Repeated Cross Sectional Surveys

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The Cochran-Armitage trend test can be used to assess time trends in prevalence of outcomes across repeated cross-sectional surveys. Sample size Calculation in Stata Statistics > Power and Sample Size > Outcome > Binary > Linear Trend in proportions in Jx2 table OR power trend Examples follow Sample size for

Multi-level Model in Stata – basic syntax for ‘mixed’

Commands used - xtmixed (older versions, aslo used in Sophia Rabe-hesketh book) or mixed (Stata 15 and newer). By default, xtmixed includes a random intercept Model Specification Outcome variableFixed Effects part of the model- double pipe - ||Random part of the modelCluster identfier - example subject id within whom the

Stata Date – Time calculations

Stata stores and saves date and time as numeric intervals referenced from 1 Jan 1960 (01jan1960 = 0) When the variable is time, one should use double variable type When variable is date, float is OK Stata help The above command is your best resource! Stata Internal Format (SIF) and